# Curtis Howland

Curtis Howland shares paid-advertising and growth advice for premium ecommerce brands, including Meta and Google ads, AI search visibility, and campaign measurement.

- Profile: https://b2binfluencer.marketing/creators/curtis-howland/
- LinkedIn: https://www.linkedin.com/in/curtishowland
- LinkedIn followers: 21,724
- YouTube: https://www.youtube.com/channel/UCgT7Bh2uVsHAqC7f96_sEmg
- Topics: artificial-intelligence, ecommerce, paid-ads, dtc-ecommerce
- Based on 11 dated posts, latest 2026-10-07

## Summary

Curtis Howland is most useful for paid-ad and AI-search operating advice for premium ecommerce growth teams.

- Best for: Premium ecommerce brands or DTC agencies hiring a paid-ads and AI-search operator.
- Not for: Mass-market, low-AOV, impulse-led brands paying for consumer reach via sponsored videos.
- Check first: Confirm agency versus sponsorship and ask for audience demographics and post results.

### Takeaways

- AI-search audit uses 20 to 30 real buying questions in the shopper's wording.
- HexClad gets roughly half its revenue in November and December.
- Click tracking and surveys disagree about AI's role in sales.

## Main ideas

- **Click tracking misses most AI-influenced revenue**: Howland's measurement argument is that assistants send shoppers to a site without a click, so UTM and pixel attribution systematically undercount AI's contribution and surveys catch what clicks miss. Across Fairing's tracking of 158 DTC brands spending $10M to $2B a year over 104 weeks, post-purchase surveys caught 7.5 times more AI-influenced orders than click-based attribution and 10.6 times the revenue, with click methods capturing under 10% of the AI-driven revenue surveys found. Howland reports AI's share of gross merchandise value growing 12 times year over year, and argues the category you sell into changes how much this matters.
- **Answer-engine optimisation is an operator checklist, not a mystery**: Howland lays out ten concrete tasks for brands that have not started working to get cited by AI assistants. Start by harvesting 20 to 30 real buying questions from support tickets, reviews, site search and post-purchase surveys, in shoppers' own words. Enter each question word for word into ChatGPT and Google AI Mode repeatedly, logging the answers, whether the brand appeared and which sources the answer pulled. Then address the underlying conditions: keep price, availability, variants, shipping and returns in visible HTML so the Merchant Center feed matches the page; publish data only the brand holds, such as return reasons and sizing failures; and write comparison pages that name who should not buy.
- **Rebuild creative for the placement; don't reuse it unchanged**: Howland argues that the ad placement's interface dictates the edit. In-game ads on AppLovin behave differently from a Meta feed: rewarded video locks viewers in for 15 to 30 seconds in exchange for in-game currency, while interstitial ads show a three-second unskippable window before the Skip button appears. A concept proven on Meta must be recut around the placement's clock, not dropped in unchanged, and tested as a separate format.
- **Premium brands should fund the months when nobody is buying**: Howland argues that for products with a long consideration window and a concentrated buying season, flat months are when demand is built; below-target returns then are a deliberate choice, not a failure. HexClad Cookware makes roughly half its revenue in November and December, yet runs advertising from January to October at low return. October runs at a marketing efficiency ratio about 33% below the year-end target, and the 13 days before the sale run about 50% below it.
- **Growth work should be readable through an exit lens**: Howland frames part of the advice for founders rather than media buyers, and offers a DTC valuation calculator to a founder audience, introduced by the claim of having helped five DTC brands sell for $500M or more. The described tool covers a valuation engine that turns a profit and loss statement into adjusted EBITDA and low, base and high multiples; a multiple builder with eight levers, each priced in turns; the bridge from enterprise value down to the cash that actually wires, accounting for debt, working capital, inventory, fees, rollover and tax; a cost-of-capital normaliser that converts any flat fee or factor rate to a true annual rate and prices it against nine financing options; and a benchmarks tab with sourced multiple bands.
- **Teaching through named data, operator quotes and a resource handoff**: A recurring priority in how Howland writes: a post opens with a number or a named brand, moves through numbered or arrowed steps, and closes with either a question inviting comparison or an offer of a downloadable asset. Depth comes from specifics rather than opinion — channel mechanics, dollar thresholds, percentages — and from quoting the operators being written about rather than paraphrasing them.

## Work to read

- [How HexClad plans a two-month selling season](https://www.linkedin.com/posts/curtishowland_hexclad-cookware-runs-ads-at-low-revenue-activity-7511054768862175232-TYXE)
- [A ten-step guide to showing up in AI answers](https://www.linkedin.com/posts/curtishowland_i-run-a-metagoogle-ads-agency-exclusively-activity-7513591667610865664-GDCv)
- [Why click tracking and surveys disagree about AI's role in sales](https://www.linkedin.com/posts/curtishowland_fairing-tracked-ai-sales-at-158-dtc-brands-activity-7511779582031798274-MbxT)
- [Recutting creative for in-game ad placements](https://www.linkedin.com/posts/curtishowland_ive-sold-450m-of-dtc-products-i-see-a-activity-7511424499855032320-1C1R)
- [A valuation calculator built around exit terms](https://www.linkedin.com/posts/curtishowland_ive-helped-5-dtc-brands-sell-for-500m-activity-7513229146039328768-b7wu)

## Brand relationships

- **AppLovin** (mention)
- **HexClad** (mention)
- **Fairing** (mention)

## Partnerships

Curtis Howland's posts describe an agency service, not a creator sponsorship program. They say the agency runs Meta and Google ads exclusively for high eight- and nine-figure brands. Two posts offer resources rather than sponsorship packages: an AppLovin creative strategy guide distributed after a LinkedIn connection and a comment of 'creative,' and a DTC valuation calculator introduced with 'Want it? You know what to do...' These routes lead to their own guides or tools, not verified sponsored-placement menus. For a brand plan, the practical qualification is revenue scale: the agency service described in the posts is aimed at high eight- and nine-figure ecommerce businesses. Ask directly about rates, deliverables, usage rights, exclusivity, timelines, onboarding, reporting cadence, contracting terms, and the formal partnership inquiry address.

## Alternatives

- Aabhas Vijay: Choose Aabhas Vijay when a DTC growth agency's bottleneck is AI-search strategy: whether ChatGPT searches the web for the brand's category, how query fan-out works, and which sources and competitors get cited. Their posts give an agency a diagnostic sequence to run before hiring anyone: pick 5 to 10 real buyer questions, run them in ChatGPT, check whether live retrieval happens, look for fan-out searches (the post cites an average of 7.6 per prompt), and map the sources the model repeatedly finds. A second post explains why keyword-led AEO fails: optimizing for the shopper's question rather than the AI's research process, producing content around topics instead of decisions, missing the retrieval opportunity, and confusing keyword ranking with AI visibility. For a premium ecommerce brand with an unresolved AI-visibility problem, that diagnostic work is more specific than Curtis Howland's ten-step playbook.
- Grace Wright: Choose Grace Wright when the buyer needs an AI-visibility audit across a large website estate, especially for a considered-purchase or manufacturing business where the issue is whether assistants can find, trust, and quote the company—not media buying. Wright's post reports an audit of about 1,800 pages across 11 manufacturing websites, with findings ranked by frequency: missing or generic schema on 11 of 11, thin third-party corroboration on 11 of 11, pages that cannot yield a clean answer on 11 of 11, stale content on 10 of 11, contradictory facts on 9 of 11, orphaned pages and broken proof on 9 of 11, proof locked in PDFs on 8 of 11, crawlers blocked or throttled on 8 of 11, missing or JavaScript-injected H1s on 3 of 11, and live placeholder content on 2 of 11. For a premium ecommerce brand with a sprawling catalogue or legacy site, that audit method is a better first step than Curtis Howland's playbook when the root cause is technical or related to content credibility.
- Kait Stephens: Choose Kait Stephens when the decision shifts from hiring a paid-ads and AI-search operator to understanding social commerce and platform-owned transactions. Stephens's posts analyse Best Buy's arrival on TikTok Shop with nearly 10,000 products, the difference between beauty and higher-consideration categories, TikTok driving discovery and checkout while Best Buy handles fulfilment and returns, and the customer-ownership problem when a sale closes inside someone else's platform. The second post shows a brand-side digital commerce operator bringing a paid-media leader onto an advisory board for an ad platform product. It also names the measurement problem: top-line ROI without campaign-level visibility, and last-click attribution described as not worth making business decisions on. For a premium ecommerce brand weighing TikTok Shop or seeking an operator's view on paid-media measurement, that is closer to the decision than Curtis Howland's agency and AEO process posts.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/